Search Results (3,886)

Globally, Central Asian wild fruit forests are critical repositories of wild fruit germplasm resources and provide essential ecosystem services. However, their habitats are facing escalating degradation risks driven by climate warming, shifting precipitation regimes, and intensifying anthropogenic disturbances. Accurately quantifying climate-driven spatiotemporal variations in habitat suitability for keystone wild fruit tree species is therefore an essential prerequisite for formulating targeted conservation and management strategies in arid and semi-arid landscapes. In this study, we applied the maximum entropy (MaxEnt) model to simulate the current (2000–2020 baseline) and future (2030s, 2050s, 2070s) potential suitable habitats of two dominant wild fruit tree species, Malus sieversii (Ledeb.) M.Roem. and Prunus cerasifera Ehrh., in the Ili Valley, a core distribution area of Central Asian wild fruit forests in northwestern China. We integrated rigorously screened species occurrence records with key environmental predictors and characterized future climate conditions using three Shared Socioeconomic Pathways (SSPs; SSP126, SSP245, and SSP585) spanning low to high radiative forcing levels. The model exhibited excellent predictive performance (AUC > 0.85), confirming the robustness and reliability of our habitat suitability simulations. Elevation and annual precipitation were identified as the dominant environmental variables governing habitat suitability for both species, highlighting the critical role of terrain–hydroclimate interactions in maintaining viable dryland refugia for wild fruit forests. Under the baseline climate scenario, the total area of suitable habitats reached 24.014 × 10³ km² for Malus sieversii and 18.990 × 10³ km² for Prunus cerasifera. Future climate projections revealed a consistent and significant contraction trend in suitable habitats for both species, with the magnitude of habitat loss escalating with increasing radiative forcing and longer projection time horizons. Specifically, under the high-emission SSP585 scenario by the 2070s, the suitable habitat area is projected to decline by 7.579 × 10³ km² for Malus sieversii and 9.883 × 10³ km² for Prunus cerasifera relative to the baseline. Our findings delineate climate-vulnerable hotspots of wild fruit forests and provide a robust spatial scientific basis for prioritizing in situ conservation, targeted habitat restoration, and anthropogenic disturbance regulation to support the long-term persistence of these irreplaceable wild fruit germplasm resources under accelerating global climate change. Full article

Land cover (LC) change is reshaping terrestrial ecosystems and profoundly impacting sustainable development in Africa, yet the long-term, continental-scale spatiotemporal dynamics of these shifts remain obscured. To address the above issue, this study systematically explores the spatiotemporal dynamics of LC across Africa from 1985 to 2022 by leveraging the fine-resolution remote-sensing-derived GLC_FCS30D LC dataset within a stratified Intensity Analysis framework. To decompose landscape changes into interval, category, and transition levels across five climatic sub-regions of Africa, we systematically evaluate the temporal consistency of land systems. This hierarchical approach disentangles systematic transition pathways from random fluctuations, thereby revealing the distinct regional regimes governing continental transformation of LC. Our results ultimately show a strong LC change acceleration in Africa after 2010, mainly in Southern, Eastern, and Western Africa, which together made up 80 to 90% of the continent’s LC dynamics. During the whole study period, shrubland and grassland had the highest gross turnover due to their high bidirectional volatility. Intensity-wise, forest remained inactive even though it was a persistent net loser to crop in East Africa (2010–2020), to shrub in Southern Africa (1990–2022), and to wetland in West Africa during the post-2000 intervals. Wetland had a major change in dynamics from historical growth during 1985–1990 to systematic decline in 2015–2022. Cropland increased by systematically targeting shrubland and grassland, mainly in East Africa. Additionally, the Sahel contributed 40% of continental grassland to bare area transitions, despite some recovery of grassland in the region. These findings show that aggregate net-change metrics obscure the volatility in African LC; therefore, distinct regional regimes such as agricultural expansion and forest degradation necessitate spatially differentiated management strategies. Full article

Climate-induced drought and intensifying land-use pressures threaten ecosystem services and agricultural productivity, particularly in regions with distinctive soil and ecological characteristics. Alabama’s Black Belt, defined by its clay-rich soils and shaped by a legacy of plantation agriculture, uneven land tenure, and persistent socioeconomic disadvantage, is increasingly vulnerable to these interacting stressors. This study analyzes long-term (2000–2023) spatiotemporal patterns of Land Use Land Cover (LULC) change and vegetation response to drought to inform sustainable resource management. Multi-temporal Landsat imagery and National Land Cover Database (NLCD) products were used to quantify LULC dynamics. At the same time, vegetation condition and moisture stress were assessed using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI). Drought conditions were evaluated using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), which incorporates temperature-driven evaporative demand. Results indicate substantial landscape change, including declines in deciduous forest (−17.78%) and pasture/hay (−13.17%), alongside increases in medium-intensity developed land (+20.25%) and evergreen forest (+10.62%). Declining NDVI and NDMI values indicate increasing vegetation stress, particularly during prolonged droughts. Vegetation response exhibited a weak relationship with SPI (R = 0.37) but a stronger association with SPEI (R = 0.59), underscoring the importance of accounting for atmospheric water demand. These findings highlight the growing vulnerability of Black Belt ecosystems to coupled climate and land-use pressures and provide insights to strengthen climate-resilient agricultural management. Full article

Wooden, nature-based barrier structures are widely implemented after wildfire in Mediterranean forests to reduce runoff connectivity and trap sediment, yet their ecological footprint on early plant recovery remains poorly quantified in Greece. We assessed two-year vascular plant recovery in forest landscapes burned during the 2021 wildfire season (Parnitha, Attica; Mavrolimni, Corinthia/Peloponnese) using repeated field surveys in 2022 and 2023. Sixteen permanent plots were established within operational rehabilitation works and assigned to the dominant structure types: wattles (brush/branch piles), contour-oriented hillslope log barriers, and channel log dams. In each year, vascular plant composition and recovery endpoints (species richness and diversity indices, density, cover, and aboveground biomass) were quantified using standardized quadrat sampling. Vegetation cover and biomass increased strongly from 2022 to 2023 at both sites, indicating rapid early reassembly. Against this dominant year effect, structure type was associated with pronounced biodiversity and compositional differences, most clearly in Parnitha where log barriers exhibited markedly reduced diversity in 2022 and community turnover patterns differed among structures. Plot-level PERMANOVA on Bray–Curtis dissimilarities calculated from log(x + 1)-transformed abundances did not detect a statistically significant structure type effect in either year (p > 0.05), whereas descriptive Bray–Curtis heatmaps suggested compositional contrasts among structure type × year combinations. Indicator–species analysis further identified a limited set of taxa associated with specific structures, suggesting provisional structure-linked microsite filtering during early assembly. By quantifying community composition and indicator taxa alongside structural recovery, this study provides operational-scale evidence that common wooden post-fire measures may be associated with early biodiversity signals in the first two years after fire, although these patterns should be regarded as provisional given the short monitoring period and limited replication. Incorporating these signals into post-fire land management can improve intervention design and placement, aligning risk reduction with biodiversity recovery in Mediterranean landscapes. Full article

The global expansion of tree plantations has led to extensive fragmentation of natural forests, posing significant challenges for biodiversity conservation. Understanding the diversity patterns and underlying mechanisms of ground-dwelling insects in these fragmented landscapes is critical to inform effective conservation strategies. To address this, we sampled ground-dwelling insects using pitfall traps across nine remnant natural forest fragments (“islands”) embedded within a tree plantation matrix in Guangxi, China. We examined insect family-level diversity and community composition in relation to fragment isolation (low vs. high) and size (large vs. small) and explored the mechanisms driving the observed patterns. Our results revealed no significant difference in ground-dwelling insect diversity between low-isolation and high-isolation fragments. However, diversity was significantly lower in smaller fragments compared to larger ones. This reduction was primarily driven by decreased seedling density within smaller fragments, directly reflecting the adverse effects of plantation-driven fragmentation on native seedling establishment. Furthermore, we observed noble shifts in community composition of ground-dwelling insects along both fragment isolation and size gradients. Highly isolated fragments exhibited a decline in phytophagous insects and omnivores (with detritivore-herbivore diets), but an increase in detritivores. Smaller fragments exhibited consistent declines across multiple insect taxa spanning various dietary guilds. The observed changes in ground-dwelling insect composition were driven by shifts in plant (especially seedling) community composition. Our findings reveal a clear cascading effect: plantation-driven fragmentation limits native plant regeneration, and these limitations subsequently propagate to higher trophic levels, profoundly impacting ground-dwelling insects. Effective restoration of plantation-fragmented landscapes requires strategies that both prioritize the preservation of large, continuous forest fragments and promote native seedling recruitment within existing fragments. Full article

With accelerating global urbanization and increasingly diverse demands for public spaces, promoting urban low-carbon transitions and enhancing residents’ quality of life have become central missions of modern urban development. As one of the city’s primary arteries, streets—through their green landscapes, slow-moving transportation systems, and public facilities—play an indispensable role in reducing carbon emissions, promoting healthy living, and improving residents’ well-being. In this study, the Yubei District of Chongqing was selected as the research area, and an automated evaluation framework was proposed for street visual quality, based on multi-source street view data and ensemble learning. PSP-Net semantic segmentation model was employed to extract eight key visual indicators from street view images, including green view index, Visual Entropy (Entropy), sky view factor (SVF), drivable space, sidewalk, safety facilities, buildings, and enclosure. Based on these features, a Stacking-based ensemble learning model was constructed, integrating multiple base models such as Random Forest, XGBoost, and LightGBM, with Linear Regression as the meta-learner, to predict street visual quality. The results demonstrate that the ensemble model significantly outperforms any single model, achieving a correlation coefficient (r) of 0.77 and effectively capturing the complex perceptual features of street environments. This study provides a reliable, intelligent, and quantitative method for large-scale evaluation of urban street visual quality, while supplying data support and decision-making references for street renewal and spatial optimization. Full article

The interaction between environmental variables influences patterns of diversity and the composition of communities along the elevational gradient. However, there is a lack of evidence regarding how these diversity patterns in Scolytinae change in response to environmental changes associated with elevation. This study aims to evaluate the influence of environmental changes along an elevational gradient on the diversity and composition of Ambrosia beetles, testing the hypothesis that species assemblages are primarily driven by the interaction between environmental variables and vegetation structure. We sampled Scolytinae at five sites (650–3360 m a.s.l.) on Tacaná Volcano from February 2018 to January 2019. Sampling was conducted using five trap types, including ethanol-baited Malaise traps and interception traps. Data were analyzed using Hill numbers for alpha diversity, Bray–Curtis indices for beta diversity, and canonical correspondence analysis to evaluate the relationship between Scolytinae species abundance and environmental variables. We recorded a high richness with 82 species, a peak in diversity at mid-elevations in mesic montane forests (p < 0.05). The Scolytinae species pool is structured in three local assemblages, corresponding to different elevational landscapes, environmentally structured. Different environmental variables displayed some correlation with species dynamics. However, these factors alone were insufficient to explain patterns of species diversity. Their influence appears to depend on interactions with site-specific characteristics. These results highlight that elevational gradients act as environmental filters structuring Scolytinae assemblages primarily through species turnover rather than nested species loss. Full article

Spatio-temporal analysis of land cover (LC) dynamics is essential for understanding landscape transformation in semi-arid woodland ecosystems. This study assessed historical and projected land cover changes in the Elnour Natural Forest Reserve (ENFR), Sudan, from 1995 to 2060. Historical maps for 1995, 2008, and 2021 were generated using a Random Forest classifier, while future scenarios for 2034, 2047, and 2060 were simulated using a Cellular Automata–Artificial Neural Network (CA–ANN) model. The results show that semi-bare land expanded from 23.1% in 1995 to 40.0% in 2021, while dense woodland declined from 26.7% to 15.7%, indicating substantial structural transformation of the landscape. Open woodland exhibited partial recovery, increasing to 39.9% in 2021. Future projections indicate a moderate increase in dense woodland to 23.8% by 2060; however, semi-bare land remains the dominant class, reflecting persistent landscape instability. These findings demonstrate the coexistence of degradation and localized regeneration processes in ENFR and highlight the importance of long-term monitoring of land cover dynamics in dryland environments. The study further shows that integrating machine learning classification with spatially explicit CA–ANN modeling provides an effective framework for analyzing historical trends and exploring potential future trajectories of land cover change in data-limited semi-arid regions. Full article

The Land Use and Land Cover (LULC) of many regional landscapes are changing due to natural effects and anthropogenic activities, impacting biodiversity and ecosystem services. LULC dynamics reflect the altered flow of energy, water, and greenhouse gases, influencing the pillars of sustainability: society, environment, and economy. Thus, assessing LULC changes is vital for understanding the relationship between nature and society. This study used multi-temporal remotely sensed imagery to examine LULC change between 1990 and 2019 in the context of Forest Transition Theory (FTT) across the Greater Shawnee National Forest (GSNF) area of southern Illinois, USA, using a random forest algorithm, and projecting change to 2050 with a Land Change Model integrated with IPCC temperature and precipitation scenarios. From 1990 to 2019, LULC analysis showed increases in deciduous forest (1.35%), mixed forest (26.40%), agriculture (2.15%), and built-up areas (6.70%), while hay/grass/pasture declined (16.0%). LULC change intensity was highest from 1990 to 2001 (2.35% annually), slowing to 0.23% (2001–2010) and 0.18% (2010–2019). The overall accuracy (OA) of LULC classification ranged from 0.9 to 0.95 at a 95% confidence interval (CI). Projections to 2050 showed consistent increases in built-up areas (17.12–42.61%), water (28.75–39.70%), and hay/grass/pasture (6.23–38.38%), while overall forest cover declined in all scenarios. Deciduous forests decreased by 3.11–19.87% and were replaced by mixed forests in some scenarios (12.45–23.63%), while evergreen forests showed mixed responses, ranging from a decline of up to 17.13% to an increase of 2.90%. The OA of projected LULC ranged from 0.71 to 0.83 (95% CI) across SSP-RCP-based temperature and precipitation scenarios. The results showed that the GSNF broadly follows the FTT framework: forest recovery since 2001 coincided with rural depopulation, slow agricultural expansion, and rising incomes. However, climate change is expected to disrupt this recovery, pushing transitions toward mixed and evergreen forests. Findings demonstrate the importance of integrating remote sensing-based LULC with socio-economic trends and climate adaptation strategies to sustain forests and ecosystem services under future environmental pressures. Full article

Patterns of resource selection are driven by the decision-making processes of animals occurring at multiple scales from where to establish a home range (i.e., second order selection) to which resource patches to use within the home range (i.e., third order selection). Elk (Cervus canadensis) were reintroduced to southwestern Virginia, USA, from 2012 to 2014 following successful translocations onto reclaimed surface coal mines in the region. We sought to understand how elk have acclimated following their translocation using location data from GPS-collared adult female elk (n = 33) collected from 2019 to 2022 along with remotely sensed terrain and land cover data. We utilized continuous-time movement models paired with generalized linear mixed-effects modeling to describe seasonal resource selection at second and third orders. At both scales of selection and throughout the year, female elk selected reclaimed surface mines, conifer forests, ridgetops, and areas with lower terrain roughness, while avoiding mixed hardwood and oak (Quercus spp.) forests. Unmined open land was only selected at the third order during periods of forage scarcity (i.e., winter) and increased metabolic requirements (i.e., late gestation). Although surface coal mining leaves legacy environmental impacts on the landscape, management of these sites provides benefits to elk and maintains open habitat that is otherwise limited. Full article

Understanding how landscape structure affects nutrient pollution is essential for contemporary effective river basin management. This study examined the influence of landscape composition and configuration on concentrations of nitrate (NO₃⁻), nitrite (NO₂⁻), and ammonium (NH₄⁺) in 30 small lowland catchments of central–eastern Poland during the cold period. Water samples were collected monthly from September 2021 to April 2022, and land-use patterns were quantified using landscape metrics derived from high-resolution spatial data at the catchment scale and within riparian buffer zones. The results showed that the impact of land use on nitrogen concentrations was strongly dependent on both landscape type and spatial scale. Forests, meadows, wetlands, and water bodies generally acted as sink landscapes, reducing nitrate and nitrite levels. The effect was more pronounced in catchments where forest patches (mainly coniferous) covered a larger area, had greater total Edge Length, and were more complex in shape. It was advantageous when meadow patches were large, cohesive, and weakly fragmented. In contrast, arable land and built-up areas consistently functioned as source landscapes, contributing to higher nitrogen concentrations when characterized by a larger share, size (both), and aggregation degree of patches (arable land). Higher landscape diversity at the catchment scale was associated with lower nitrate and nitrite concentrations. Overall, land-use effects were best explained at larger spatial extents, especially the entire catchment and the 500 m buffer zone. These findings emphasize the need to integrate landscape structure and appropriate spatial scale into nutrient management strategies for lowland agricultural catchments. Full article

Tick-borne diseases are an increasing public health concern in Europe, driven by climate change, landscape transformation, and expanding human activity. Urban green spaces provide suitable habitats for ticks and increase human exposure to tick-borne pathogens (TBPs), yet habitat-specific patterns in urban and suburban environments remain poorly characterized. This study examined tick distribution and TBPs prevalence across 11 urban and suburban sites in Kaunas County, Lithuania. A total of 1539 questing Ixodes ricinus ticks were collected and screened by real-time PCR for Borrelia spp., Anaplasma phagocytophilum, Neoehrlichia mikurensis, Rickettsia spp., and Babesia spp., with further species identification by sequencing. Borrelia spp. were most prevalent (24.43%), followed by Rickettsia spp. (7.60%), N. mikurensis (6.63%), A. phagocytophilum (3.64%), and Babesia spp. (2.53%). Tick density, pathogen prevalence, and species diversity varied among habitats, with higher values in forested and ecotonal areas, but notable infection rates were also observed in managed urban sites. Co-infections occurred in 18.8% of infected ticks. Our findings demonstrate that the circulation of TBPs in urban and suburban landscapes is shaped by local habitat features, host communities, and management intensity, highlighting the need for habitat-specific risk assessment in urban planning and public health. Full article

Live Fuel Moisture Content (LFMC) is a key determinant of vegetation flammability and fire behaviour, yet LFMC products have traditionally relied on coarse-resolution sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS, 500 m), limiting their utility for fine-scale fire management. This study introduces the first continental-scale operational LFMC product for Australia derived from Sentinel-2 imagery at 20 m resolution. We developed a Random Forest regression model trained on approximately 680,000 paired Sentinel-2 reflectance and MODIS-LFMC samples (2015–2022) to emulate outputs from the Australian Flammability Monitoring System (AFMS), a MODIS-based pre-operational LFMC product. Model evaluation against AFMS showed strong agreement for grasslands (R² = 0.83, RMSE = 32.45%) and moderate performance for forests (R² = 0.43, RMSE = 20.84%) and shrublands (R² = 0.21, RMSE = 10.28%). Validation using 2279 in situ LFMC measurements from Globe-LFMC 2.0 indicated improved accuracy at homogeneous sites (NDVI CV ≤ 20th percentile: R² = 0.42, RMSE = 31.39%). Additionally, when validating with a dedicated field campaign specifically designed for Sentinel-2 LFMC assessment, the model achieved its highest accuracy (R² = 0.53, RMSE = 32.14%), highlighting the importance of tailored ground protocols for satellite product validation. Predicted LFMC also reproduced observed seasonal dynamics at sites with frequent field monitoring. Despite variability across vegetation types, the Sentinel-2 LFMC product effectively captured spatial patterns and seasonal dynamics, providing a step change in monitoring vegetation moisture at landscape scales. This high-resolution dataset offers actionable intelligence for prescribed burning, fuel treatment planning, and fire behaviour modelling in fire-prone environments. Full article

Forest structure is fundamental for linking ecological processes with management outcomes, and it influences key ecosystem services. However, the high cost and complexity of field data collection often limit the application of structural indices to small-scale studies, constraining operational assessments of forest multifunctionality. This study develops and tests an operational indicator of forest multifunctionality based on the structural heterogeneity index derived from forest management plans (FMPs). We analyzed the dendrometric data from 134 management units across 15 FMPs in the Lombardy region (Italy). Horizontal diversity was quantified using a Gini-based index, calculated from tree diameter-class distributions and combined with stand age, timber stock, and tree density using principal component analysis. Two orthogonal gradients emerged: a productivity gradient and a maturity–structural heterogeneity gradient. Generalized linear mixed models were used to assess their effects on carbon sequestration, timber yield, and touristic–recreational value. Structural heterogeneity was positively associated with all three functions, while productivity showed contrasting effects, particularly a negative relationship with recreational value. These results demonstrate that structural complexity and productivity are not necessarily in conflict and highlight the potential of FMPs as cost-effective data sources for operational, landscape-scale assessments of forest multifunctionality. Full article

Phytophthora cinnamomi Rands, an oomycete pathogen of global relevance, is a major driver of cork oak (Quercus suber L.) decline and mortality in Mediterranean forests. Its management remains challenging in multifunctional landscapes where forestry and agriculture intersect, such as Mediterranean oak dehesas. Conventional fungicides are used against P. cinnamomi, but their negative environmental impacts underscore the need for alternative management in agroforestry systems. This study evaluated whether a commercially available microbial biostimulant, VESTA, enhances physiological performance and mitigates pathogen pressure in Q. suber. Seedlings were inoculated with P. cinnamomi and treated with the bioinoculant via fertigation or watering to substrate saturation, under controlled greenhouse conditions. Plant physiological parameters and soil oomycete inoculum concentrations were measured to assess treatment efficacy. Both application methods significantly improved physiological performance in inoculated and mock-inoculated plants. Photosynthesis, stomatal regulation, and water balance were most affected. Quantitative PCR analyses revealed a strong pathogen reduction, with DNA concentrations approximately tenfold lower in treated substrates (~0.001 ng mL⁻¹) than untreated controls (~0.011 ng mL⁻¹). Overall, the product enhanced Q. suber resilience by improving plant physiological responses and reducing pathogen abundance, supporting its potential as a bio-based tool for nurseries and restoration in Mediterranean ecosystems. Field studies are needed to validate these findings under natural variability and optimize long-term application strategies. Full article